Christoph: /* External links */

2017-03-30T23:53:42Z

‎External links

Christoph: Created page with "'''matplotlib''' is a plotting library for the Python programming language and its numerical mathematics extension NumPy. ==Examples==

 import matplotl..."

2017-03-30T22:21:24Z

Created page with "'''matplotlib''' is a plotting library for the Python programming language and its numerical mathematics extension NumPy. ==Examples== <pre> import matplotl..."

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'''matplotlib''' is a plotting library for the Python programming language and its numerical mathematics extension [[Python/NumPy|NumPy]].

==Examples==

<pre>
import matplotlib.pyplot as plt
import numpy as np
</pre>

;Simple plot
<pre>
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 10, 10) # start, end, num points in-between
y = np.sin(x)
plt.plot(x, y)
plt.show()

# Add labels
plt.plot(x, y)
plt.xlabel("Time")
plt.ylabel("Some function of time")
plt.title("Example plot")
plt.show()

# Increase number of points in-between
x = np.linspace(0, 10, 100)
y = np.sin(x)
plt.plot(x,y)
plt.show() # => much smoother line
</pre>

; Scatter plots
<pre>
import os
os.chdir('../linear_regression_class/')
import pandas as pd
A = pd.read_csv('data_1d.csv', header=None).as_matrix()
A.head()
A.info
A.shape
x = A[:,0]
y = A[:,1]
plt.scatter(x, y)
plt.show()

x_line = np.linspace(0, 100, 100)
y_line = 2*x_line + 1
plt.scatter(x, y)
plt.plot(x_line, y_line)
plt.show()
</pre>

; Histograms
<pre>
# Using same data from above
plt.hist(x)
R = np.random.random(10000)
plt.hist(R)
plt.show()
plt.hist(R, bins=20)
plt.show()

# normally distributed
y_actual = 2*x + 1
residuals = y - y_actual
plt.hist(residuals)
plt.show()
# more-or-less a bell curve (with so few data points)
</pre>

; Plotting images
* An image is just a matrix of numbers
* A(i,j) represents the pixel intensity at coordinate (i,j)
* JPG or PNG are not matrices because they are compressed
* Decompress them to get back a matrix
* In this example, we will use the [[:wikipedia:MNIST_database|MNIST dataset]] (handwritten digits, 0-9)
** [https://www.kaggle.com/c/digit-recognizer Digit Recognizer] via Kaggle
** Download the "train.csv" file
* 28x28 = 784 pixels => 784 columns in CSV file
<pre>
import pandas as pd

df = pd.read_csv("train.csv")
df.shape # => (42000, 785)

M = df.as_matrix()

M[0,0] # => digit "1"
im = M[0, 1:] # get 0th row and all columns except column 0
im.shape
im = im.reshape(28, 28)
im.shape
plt.imshow(im)
plt.show()

plt.imshow(im, cmap='gray')
plt.show()
plt.imshow(255 - im, cmap='gray')
plt.show()

M[20,0] # => digit "8"
im = M[20, 1:]
im.shape
im = im.reshape(28, 28)
plt.imshow(255 - im, cmap='gray')
plt.show()
</pre>

==See also==
* [[Python/NumPy|NumPy]]
* [[Python/SciPy|SciPy]]
* [[Python/pandas|pandas]]
* scikit-learn
* scikit-image

==External links==
*[http://matplotlib.org/ Official website]

[[Category:Scripting languages]]

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	[[Category:Scripting languages]]		[[Category:Scripting languages]]
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Python/matplotlib - Revision history

Christoph: /* External links */

Christoph: Created page with "'''matplotlib''' is a plotting library for the Python programming language and its numerical mathematics extension NumPy. ==Examples==
import matplotl..."